[Antidiabetic treatments for the elderly]. / Les traitements antidiabétiques chez le sujet âgé.

Diabetes is very common in people over 75. A broad arsenal of treatments is now available. It is important, however, to choose the right treatment regimen to suit the patient's specific glycemic targets.

Situational analysis of diabetic retinopathy treatment Services in Ghana.

BACKGROUND: Although the equitable distribution of diabetic retinopathy (DR) services across Ghana remains paramount, there is currently a poor understanding of nationwide DR treatment services. This study aims to conduct a situation analysis of DR treatment services in Ghana and provide evidence on the breadth, coverage, workload, and gaps in service delivery for DR treatment. METHODS: A cross-sectional study was designed to identify health facilities which treat DR in Ghana from June 2018 to August 2018. Data were obtained from the facilities using a semi-structured questionnaire which included questions identifying human resources involved in DR treatment, location of health facilities with laser, vitreoretinal surgery and Anti-vascular endothelial growth factor therapy (Anti-VEGF) for DR treatment, service utilisation and workload at these facilities, and the average price of DR treatment in these facilities. RESULTS: Fourteen facilities offer DR treatment in Ghana; four in the public sector, seven in the private sector and three in the Christian Health Association of Ghana (CHAG) centres. There was a huge disparity in the distribution of facilities offering DR services, the eye care cadre, workload, and DR treatment service (retinal laser, Anti-VEGF, and vitreoretinal surgery). The retinal laser treatment price was independent of all variables (facility type, settings, regions, and National Health Insurance Scheme coverage). However, settings (p = 0.028) and geographical regions (p = 0.010) were significantly associated with anti-VEGF treatment price per eye. CONCLUSION: Our results suggest a disproportionate distribution of DR services in Ghana. Hence, there should be a strategic development and implementation of an eye care plan to ensure the widespread provision of DR services to the disadvantaged population as we aim towards a disadvantaged population as we aim towards a universal health coverage.

Treatment of type 2 diabetes mellitus in the elderly - Special considerations.

Type 2 diabetes is a frequent chronic disease. Given its strong positive association with older age, it is a significant public health issue in elderly populations. Furthermore, the aging of the population, driven by increasing life expectancy in high and middle-income countries leads to an increasing prevalence of diabetes.Although the same diagnostic criteria apply to the elderly and to younger people, there are unique aspects to the care for elderly type 2 diabetes patients. Both treatment goals and preferred medications, as well as non-pharmacological approaches should be adjusted in the elderly. For example, increasing the amount of physical activity may encounter difficulties, while introducing an appropriate diet may be more challenging. The patients' therapeutic adherence requires special attention due to cognitive and physical limitations. The most important treatment goal is to avoid hypoglycemia. Frailty, social and economic issues, comorbidities and the consequent polypharmacy frequently causing drug-drug interactions, as well as the increased danger of drug toxicity due to renal failure are only some of the problems that make the health care for old diabetes patients extremely difficult. Adequate care requires cooperation from a multidisciplinary team of health care professionals.Acute diabetes complications have a higher mortality in the elderly, thus close attention must be paid to avoid them. Family members should be involved in the care of elderly diabetes patients, and it is recommended to educate them on clinical signs of complications. Regular care for the patients including feedback on quality of life and early signs of health issues are essential.

Controlled Interfacial Polymer Self-Assembly Coordinates Ultrahigh Drug Loading and Zero-Order Release in Particles Prepared under Continuous Flow.

Microparticles are successfully engineered through controlled interfacial self-assembly of polymers to harmonize ultrahigh drug loading with zero-order release of protein payloads. To address their poor miscibility with carrier materials, protein molecules are transformed into nanoparticles, whose surfaces are covered with polymer molecules. This polymer layer hinders the transfer of cargo nanoparticles from oil to water, achieving superior encapsulation efficiency (up to 99.9%). To control payload release, the polymer density at the oil-water interface is enhanced, forming a compact shell for microparticles. The resultant microparticles can harvest up to 49.9% mass fraction of proteins with zero-order release kinetics in vivo, enabling an efficient glycemic control in type 1 diabetes. Moreover, the precise control of engineering process offered through continuous flow results in high batch-to-batch reproducibility and, ultimately, excellent scale-up feasibility.

Identification of People with Diabetes Treatment through Lipids Profile Using Machine Learning Algorithms.

Diabetes incidence has been a problem, because according with the World Health Organization and the International Diabetes Federation, the number of people with this disease is increasing very fast all over the world. Diabetic treatment is important to prevent the development of several complications, also lipid profile monitoring is important. For that reason the aim of this work is the implementation of machine learning algorithms that are able to classify cases, that corresponds to patients diagnosed with diabetes that have diabetes treatment, and controls that refers to subjects who do not have diabetes treatment but some of them have diabetes, bases on lipids profile levels. Logistic regression, K-nearest neighbor, decision trees and random forest were implemented, all of them were evaluated with accuracy, sensitivity, specificity and AUC-ROC curve metrics. Artificial neural network obtain an acurracy of 0.685 and an AUC value of 0.750, logistic regression achieve an accuracy of 0.729 and an AUC value of 0.795, K-nearest neighbor gets an accuracy of 0.669 and an AUC value of 0.709, on the other hand, decision tree reached an accuracy pg 0.691 and a AUC value of 0.683, finally random forest achieve an accuracy of 0.704 and an AUC curve of 0.776. The performance of all models was statistically significant, but the best performance model for this problem corresponds to logistic regression.

Types of diabetes during pregnancy and longitudinal BMI in offspring from birth to age 10 years.

OBJECTIVE: To examine longitudinal BMI trajectory from birth to age 10 years in a clinical cohort after exposure to maternal pre-existing type 1 (T1D), type 2 (T2D), gestational diabetes managed with or without anti-diabetes medication, and no diabetes during pregnancy. METHODS: Data included 218 227 singleton children born in 2008-2015 from a population-based integrated healthcare system; 537 exposed to maternal T1D, 7836 to T2D, 6982 to medicated GDM and 12 576 to unmedicated GDM. Differences in BMI over time among groups were assessed by non-linear mixed-effects models adjusting for covariates. RESULTS: Children's BMI was significantly lower 6-months after birth for all diabetes exposed groups compared to no diabetes. Beginning at approximately age 2.5 years, BMI was significantly higher for T1D, T2D and medicated GDM groups compared to the no diabetes group. At age 3, the growth pattern started separating with highest BMI in T1D and T2D groups, followed by medicated GDM, unmedicated GDM, and the no diabetes groups. By age 7, BMI was significantly higher for the unmedicated GDM group compared to the no diabetes group. Adjusted BMI was generally comparable between T1D and T2D groups for all ages. Starting at age 5, T1D, T2D and medicated GDM groups had BMI greater than one SD over the BMI in the no diabetes group. CONCLUSION: In a clinical cohort with standard diabetes management approaches, a hierarchical BMI growth pattern exists in offspring exposed to different types of diabetes during pregnancy after adjusting for important covariates, starting as early as age 3 years.

Oral insulin delivery by carboxymethyl-ß-cyclodextrin-grafted chitosan nanoparticles for improving diabetic treatment.

In this paper, a new oral insulin formulation, insulin-loaded carboxymethyl-ß-cyclodextrin-grafted chitosan nanoparticles (insulin/CMCD-g-CS NPs), was fabricated by ionic crosslinking technique. The therapeutic efficacy of new formulation was investigated in detail. Firstly, the CMCD-g-CS was synthesized by EDC-mediated esterification reaction. The prepared CMCD-g-CS exhibited favourable loading capacity and encapsulation efficiency of drug. The release experiment in vitro showed that the nanocarrier could efficiently protect encapsulated insulin at simulated gastric environment and release drug in the simulated colonic fluid. The insulin/CMCD-g-CS NPs effectively promoted drug internalization into Caco-2 cells and could reversibly open the tight junction between cells. The oral administration of insulin/CMCD-g-CS NPs could lastingly decrease blood sugar level in diabetic mice. The liver function study verified that the insulin/CMCD-g-CS NPs had not obvious toxicity to experimental mice. Therefore, the CMCD-g-CS could be an effective and safe oral insulin delivery carrier for future clinical application. A new biocompatible polysaccharide nanoparticle was fabricated as oral insulin delivery carrier for improving diabetic treatment.

Association of Pioglitazone with Increased Risk of Prostate Cancer and Pancreatic Cancer: A Functional Network Study.

INTRODUCTION: The question of whether pioglitazone, an antidiabetic drug, increases the risk of cancer has been debated for some time. Recent studies have shown that pioglitazone use can increase the risk of prostate cancer as well as pancreatic cancer. However, it is unclear whether pioglitazone is a causal risk factor for these cancers. METHODS: In this study, we aimed to explore the direct targets of pioglitazone and genes associated with this drug by querying open platforms in order to construct a biological function network, and then to further evaluate the relationships of pioglitazone with prostate cancer and pancreatic cancer. RESULTS: We first tested our hypothesis using DrugBank and STRING. We identified four direct targets of pioglitazone and 50 pioglitazone-associated genes, which were then selected for KEGG pathway analysis using STRING and WebGestalt. This analysis generated the top 25 KEGG pathways, among which four pathways were related to site-specific cancers, including prostate cancer and pancreatic cancer. Finally, a genomic study using cBioPortal indicated that genomic alterations of two gene sets related to the prostate cancer and pancreatic cancer pathways, respectively, are associated with the acceleration of carcinogenesis. CONCLUSIONS: Pioglitazone is likely to be a causal risk factor for prostate cancer and pancreatic cancer, so this drug should be used with caution. The present research also demonstrates the use of biological function network analysis to effectively explore drug interactions and drug safety profiles.

Factors associated with Prolonged Inaction in the hypoglycaemic treatment in people with non-insulin dependent Type 2 Diabetes and elevated glycated haemoglobin: A registry-based cohort study.

AIMS: To assess factors associated with Prolonged Inaction (PI) in insulin-naïve patients with Type 2 Diabetes Mellitus (T2DM). PI was defined as the absence of treatment initiation or intensification for ≥12 months despite HbA1c >7% (53mmol/mol). METHODS: A retrospective cohort study was conducted based on data from Intego, a Flemish General Practice registry. The study period ranged from January 1, 2006 to December 31, 2013. Patients with insulin therapy before the start of the study period were excluded from the analysis. A mixed effects logistic regression was used to assess the association of PI with the presence of co-morbidities, co-medications, process parameters and bio-clinical parameters. RESULTS: In a population of 2265 patients with T2DM, 578 insulin-naive patients presented with an HbA1c >7% (53mmol/mol) for ≥12 months. Median follow-up was 1.2 years, median age 67 years, 55% were male. PI was present in 340 patients (59%) and associated with moderate to severe Chronic Kidney Disease, absence of a mental health disorder, less frequent HbA1c measurements, lower HbA1c values and a smaller number of co-medications. CONCLUSIONS: PI is highly prevalent in primary care, particularly in patients with less complex disease status and with less intensive follow-up.

Requirements for multi-level systems pharmacology models to reach end-usage: the case of type 2 diabetes.

We are currently in the middle of a major shift in biomedical research: unprecedented and rapidly growing amounts of data may be obtained today, from in vitro, in vivo and clinical studies, at molecular, physiological and clinical levels. To make use of these large-scale, multi-level datasets, corresponding multi-level mathematical models are needed, i.e. models that simultaneously capture multiple layers of the biological, physiological and disease-level organization (also referred to as quantitative systems pharmacology-QSP-models). However, today's multi-level models are not yet embedded in end-usage applications, neither in drug research and development nor in the clinic. Given the expectations and claims made historically, this seemingly slow adoption may seem surprising. Therefore, we herein consider a specific example-type 2 diabetes-and critically review the current status and identify key remaining steps for these models to become mainstream in the future. This overview reveals how, today, we may use models to ask scientific questions concerning, e.g., the cellular origin of insulin resistance, and how this translates to the whole-body level and short-term meal responses. However, before these multi-level models can become truly useful, they need to be linked with the capabilities of other important existing models, in order to make them 'personalized' (e.g. specific to certain patient phenotypes) and capable of describing long-term disease progression. To be useful in drug development, it is also critical that the developed models and their underlying data and assumptions are easily accessible. For clinical end-usage, in addition, model links to decision-support systems combined with the engagement of other disciplines are needed to create user-friendly and cost-efficient software packages.

A brief review on anti diabetic plants: Global distribution, active ingredients, extraction techniques and acting mechanisms.

A study has been conducted with the aim to provide researchers with general information on anti diabetic extracts based on relevant research articles collected from 34 reliable medical journals. The study showed that Asian and African continents have 56% and 17% share of the worldwide distribution of therapeutic herbal plants, respectively. In Asia, India and China are the leading countries in herbal plants research, and there has been an increase in medicinal research on plants extract for diabetes treatment since 1995 in these regions. The information collected shows that plant leaves are about 20% more favorable for storing active ingredients, as compared to other parts of herbal plants. A brief review on the extraction techniques for the mentioned parts is also included. Furthermore, the acting mechanisms for the anti diabetic activity were described, and the related active ingredients were identified. The findings reveal that most of the anti diabetic research is focused on the alteration of glucose metabolism to prevent diabetes.